Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit [W] is highly overall correlated with HourCounters Average GridOn Avg. [h]High correlation
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°] and 2 other fieldsHigh correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 2 other fieldsHigh correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 8 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production ReactivePower StdDev [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 3 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 3 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with Active power limit [W] and 1 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 3 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (61.0%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (53.4%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (55.1%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (56.9%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (70.5%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (75.2%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (76.1%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (77.2%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (58.4%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (80.9%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (76.1%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (60.0%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (61.8%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (76.9%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (66.7%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (65.4%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (60.0%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (58.2%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (52.1%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (54.3%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (59.1%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (90.4%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (85.8%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.6%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (71.2%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (80.7%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (83.5%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (57.6%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (77.0%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (70.4%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.4%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.4%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.9%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (91.6%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (76.5%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (75.8%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (75.8%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (71.7%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (69.5%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (51.5%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (74.8%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (56.7%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (81.9%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (77.0%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (76.9%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (79.4%) Imbalance
Active power limit [W] is highly imbalanced (98.6%) Imbalance
Active power limit source is highly imbalanced (99.8%) Imbalance
Power factor set point is highly imbalanced (99.8%) Imbalance
Power factor set point source is highly imbalanced (99.8%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (89.4%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (75.7%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (77.2%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (56.5%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (66.7%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (68.7%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (54.8%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (56.0%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (57.9%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (82.9%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (78.0%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (82.1%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (98.8%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (97.7%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (97.2%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (94.7%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (80.0%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (62.1%) Imbalance
HourCounters Average Yaw Avg. [h] is highly imbalanced (54.5%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (98.1%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (95.4%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (65.6%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (94.7%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (68.6%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (83.0%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (74.4%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (77.3%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (66.9%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (56.8%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (57.7%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.8%) Imbalance
Total Active power [W] is highly imbalanced (94.9%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (95.4%) Imbalance
Total reactive power [var] is highly imbalanced (93.7%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-15 12:18:28.178437
Analysis finished2025-05-15 12:18:58.077717
Duration29.9 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-15T14:18:58.117722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-15T14:18:58.201969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24204 
1
 
2004

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24204
92.4%
1 2004
 
7.6%

Length

2025-05-15T14:18:58.277593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.313459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24204
92.4%
1 2004
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24204
92.4%
1 2004
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24204
92.4%
1 2004
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24204
92.4%
1 2004
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24204
92.4%
1 2004
 
7.6%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23612 
1
2596 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23612
90.1%
1 2596
 
9.9%

Length

2025-05-15T14:18:58.356112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.394360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23612
90.1%
1 2596
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 23612
90.1%
1 2596
 
9.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23612
90.1%
1 2596
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23612
90.1%
1 2596
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23612
90.1%
1 2596
 
9.9%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23752 
1
2456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Length

2025-05-15T14:18:58.438619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.475291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23891 
1
 
2317

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23891
91.2%
1 2317
 
8.8%

Length

2025-05-15T14:18:58.521439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.558014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23891
91.2%
1 2317
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 23891
91.2%
1 2317
 
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23891
91.2%
1 2317
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23891
91.2%
1 2317
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23891
91.2%
1 2317
 
8.8%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24842 
1
 
1366

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24842
94.8%
1 1366
 
5.2%

Length

2025-05-15T14:18:58.602641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.640749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24842
94.8%
1 1366
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24842
94.8%
1 1366
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24842
94.8%
1 1366
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24842
94.8%
1 1366
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24842
94.8%
1 1366
 
5.2%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25125 
1
 
1083

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Length

2025-05-15T14:18:58.683885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.720547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25177 
1
 
1031

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25177
96.1%
1 1031
 
3.9%

Length

2025-05-15T14:18:58.765023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:58.801264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25177
96.1%
1 1031
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25177
96.1%
1 1031
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25177
96.1%
1 1031
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25177
96.1%
1 1031
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25177
96.1%
1 1031
 
3.9%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25242 
1
 
966

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Length

2025-05-15T14:18:58.843638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.040010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25242
96.3%
1 966
 
3.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24008 
1
 
2200

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24008
91.6%
1 2200
 
8.4%

Length

2025-05-15T14:18:59.082727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.119174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24008
91.6%
1 2200
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24008
91.6%
1 2200
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24008
91.6%
1 2200
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24008
91.6%
1 2200
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24008
91.6%
1 2200
 
8.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25438 
1
 
770

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25438
97.1%
1 770
 
2.9%

Length

2025-05-15T14:18:59.164791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.200731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25438
97.1%
1 770
 
2.9%

Most occurring characters

ValueCountFrequency (%)
0 25438
97.1%
1 770
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25438
97.1%
1 770
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25438
97.1%
1 770
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25438
97.1%
1 770
 
2.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21335 
1
4873 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21335
81.4%
1 4873
 
18.6%

Length

2025-05-15T14:18:59.243341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.281346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21335
81.4%
1 4873
 
18.6%

Most occurring characters

ValueCountFrequency (%)
0 21335
81.4%
1 4873
 
18.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21335
81.4%
1 4873
 
18.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21335
81.4%
1 4873
 
18.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21335
81.4%
1 4873
 
18.6%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25176 
1
 
1032

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25176
96.1%
1 1032
 
3.9%

Length

2025-05-15T14:18:59.325759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.361863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25176
96.1%
1 1032
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25176
96.1%
1 1032
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25176
96.1%
1 1032
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25176
96.1%
1 1032
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25176
96.1%
1 1032
 
3.9%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:18:59.406187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.439838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:18:59.479451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.514518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24128 
1
 
2080

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Length

2025-05-15T14:18:59.554281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.590015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring characters

ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24262 
1
 
1946

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24262
92.6%
1 1946
 
7.4%

Length

2025-05-15T14:18:59.633883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.669997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24262
92.6%
1 1946
 
7.4%

Most occurring characters

ValueCountFrequency (%)
0 24262
92.6%
1 1946
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24262
92.6%
1 1946
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24262
92.6%
1 1946
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24262
92.6%
1 1946
 
7.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:18:59.714037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.747777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25226 
1
 
982

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Length

2025-05-15T14:18:59.787366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.825194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24596 
1
 
1612

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Length

2025-05-15T14:18:59.868253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.904484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24508 
1
 
1700

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24508
93.5%
1 1700
 
6.5%

Length

2025-05-15T14:18:59.949547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:18:59.985659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24508
93.5%
1 1700
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24508
93.5%
1 1700
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24508
93.5%
1 1700
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24508
93.5%
1 1700
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24508
93.5%
1 1700
 
6.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24128 
1
 
2080

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Length

2025-05-15T14:19:00.029105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.067193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring characters

ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24128
92.1%
1 2080
 
7.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23995 
1
 
2213

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23995
91.6%
1 2213
 
8.4%

Length

2025-05-15T14:19:00.110136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.146934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23995
91.6%
1 2213
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 23995
91.6%
1 2213
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23995
91.6%
1 2213
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23995
91.6%
1 2213
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23995
91.6%
1 2213
 
8.4%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23502 
1
2706 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23502
89.7%
1 2706
 
10.3%

Length

2025-05-15T14:19:00.193864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.230893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23502
89.7%
1 2706
 
10.3%

Most occurring characters

ValueCountFrequency (%)
0 23502
89.7%
1 2706
 
10.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23502
89.7%
1 2706
 
10.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23502
89.7%
1 2706
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23502
89.7%
1 2706
 
10.3%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23684 
1
2524 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Length

2025-05-15T14:19:00.275580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.314341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23032 
1
3176 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23032
87.9%
1 3176
 
12.1%

Length

2025-05-15T14:19:00.359537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.396455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23032
87.9%
1 3176
 
12.1%

Most occurring characters

ValueCountFrequency (%)
0 23032
87.9%
1 3176
 
12.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23032
87.9%
1 3176
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23032
87.9%
1 3176
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23032
87.9%
1 3176
 
12.1%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24061 
1
 
2147

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24061
91.8%
1 2147
 
8.2%

Length

2025-05-15T14:19:00.443272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.480144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24061
91.8%
1 2147
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 24061
91.8%
1 2147
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24061
91.8%
1 2147
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24061
91.8%
1 2147
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24061
91.8%
1 2147
 
8.2%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23081 
1
3127 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23081
88.1%
1 3127
 
11.9%

Length

2025-05-15T14:19:00.524646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.563329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23081
88.1%
1 3127
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23081
88.1%
1 3127
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23081
88.1%
1 3127
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23081
88.1%
1 3127
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23081
88.1%
1 3127
 
11.9%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25884 
1
 
324

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Length

2025-05-15T14:19:00.608445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.645064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25884
98.8%
1 324
 
1.2%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25679 
1
 
529

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25679
98.0%
1 529
 
2.0%

Length

2025-05-15T14:19:00.690286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.726722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25679
98.0%
1 529
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25679
98.0%
1 529
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25679
98.0%
1 529
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25679
98.0%
1 529
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25679
98.0%
1 529
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25932 
1
 
276

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25932
98.9%
1 276
 
1.1%

Length

2025-05-15T14:19:00.769450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.807276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25932
98.9%
1 276
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25932
98.9%
1 276
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25932
98.9%
1 276
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25932
98.9%
1 276
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25932
98.9%
1 276
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24885 
1
 
1323

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24885
95.0%
1 1323
 
5.0%

Length

2025-05-15T14:19:00.850598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.886663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24885
95.0%
1 1323
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24885
95.0%
1 1323
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24885
95.0%
1 1323
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24885
95.0%
1 1323
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24885
95.0%
1 1323
 
5.0%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25427 
1
 
781

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25427
97.0%
1 781
 
3.0%

Length

2025-05-15T14:19:00.931695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:00.969303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25427
97.0%
1 781
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25427
97.0%
1 781
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25427
97.0%
1 781
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25427
97.0%
1 781
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25427
97.0%
1 781
 
3.0%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25571 
1
 
637

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25571
97.6%
1 637
 
2.4%

Length

2025-05-15T14:19:01.012392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.050575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25571
97.6%
1 637
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25571
97.6%
1 637
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25571
97.6%
1 637
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25571
97.6%
1 637
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25571
97.6%
1 637
 
2.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22937 
1
3271 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Length

2025-05-15T14:19:01.093947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.130931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:01.178630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.213054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23950 
1
 
2258

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Length

2025-05-15T14:19:01.253259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.292167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23263 
1
2945 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23263
88.8%
1 2945
 
11.2%

Length

2025-05-15T14:19:01.337117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.374721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23263
88.8%
1 2945
 
11.2%

Most occurring characters

ValueCountFrequency (%)
0 23263
88.8%
1 2945
 
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23263
88.8%
1 2945
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23263
88.8%
1 2945
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23263
88.8%
1 2945
 
11.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22908 
1
3300 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22908
87.4%
1 3300
 
12.6%

Length

2025-05-15T14:19:01.421610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.458426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22908
87.4%
1 3300
 
12.6%

Most occurring characters

ValueCountFrequency (%)
0 22908
87.4%
1 3300
 
12.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22908
87.4%
1 3300
 
12.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22908
87.4%
1 3300
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22908
87.4%
1 3300
 
12.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22937 
1
3271 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Length

2025-05-15T14:19:01.503289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.541941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22937
87.5%
1 3271
 
12.5%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25230 
1
 
978

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Length

2025-05-15T14:19:01.587017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.623070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25230
96.3%
1 978
 
3.7%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24837 
1
 
1371

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24837
94.8%
1 1371
 
5.2%

Length

2025-05-15T14:19:01.667881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.704740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24837
94.8%
1 1371
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24837
94.8%
1 1371
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24837
94.8%
1 1371
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24837
94.8%
1 1371
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24837
94.8%
1 1371
 
5.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26074 
1
 
134

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Length

2025-05-15T14:19:01.747482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.785375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25963 
1
 
245

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25963
99.1%
1 245
 
0.9%

Length

2025-05-15T14:19:01.828495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:01.864649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25963
99.1%
1 245
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25963
99.1%
1 245
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25963
99.1%
1 245
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25963
99.1%
1 245
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25963
99.1%
1 245
 
0.9%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25944 
1
 
264

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25944
99.0%
1 264
 
1.0%

Length

2025-05-15T14:19:02.059916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.098483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25944
99.0%
1 264
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25944
99.0%
1 264
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25944
99.0%
1 264
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25944
99.0%
1 264
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25944
99.0%
1 264
 
1.0%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25935 
1
 
273

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25935
99.0%
1 273
 
1.0%

Length

2025-05-15T14:19:02.140957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.178585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25935
99.0%
1 273
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25935
99.0%
1 273
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25935
99.0%
1 273
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25935
99.0%
1 273
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25935
99.0%
1 273
 
1.0%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25202 
1
 
1006

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25202
96.2%
1 1006
 
3.8%

Length

2025-05-15T14:19:02.221768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.257776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25202
96.2%
1 1006
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25202
96.2%
1 1006
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25202
96.2%
1 1006
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25202
96.2%
1 1006
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25202
96.2%
1 1006
 
3.8%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25161 
1
 
1047

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25161
96.0%
1 1047
 
4.0%

Length

2025-05-15T14:19:02.302491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.338462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25161
96.0%
1 1047
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25161
96.0%
1 1047
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25161
96.0%
1 1047
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25161
96.0%
1 1047
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25161
96.0%
1 1047
 
4.0%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25159 
1
 
1049

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25159
96.0%
1 1049
 
4.0%

Length

2025-05-15T14:19:02.381112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.418933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25159
96.0%
1 1049
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25159
96.0%
1 1049
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25159
96.0%
1 1049
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25159
96.0%
1 1049
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25159
96.0%
1 1049
 
4.0%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24921 
1
 
1287

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24921
95.1%
1 1287
 
4.9%

Length

2025-05-15T14:19:02.461813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.497854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24921
95.1%
1 1287
 
4.9%

Most occurring characters

ValueCountFrequency (%)
0 24921
95.1%
1 1287
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24921
95.1%
1 1287
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24921
95.1%
1 1287
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24921
95.1%
1 1287
 
4.9%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24779 
1
 
1429

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24779
94.5%
1 1429
 
5.5%

Length

2025-05-15T14:19:02.542311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.578957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24779
94.5%
1 1429
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24779
94.5%
1 1429
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24779
94.5%
1 1429
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24779
94.5%
1 1429
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24779
94.5%
1 1429
 
5.5%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23450 
1
2758 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23450
89.5%
1 2758
 
10.5%

Length

2025-05-15T14:19:02.623171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.660218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23450
89.5%
1 2758
 
10.5%

Most occurring characters

ValueCountFrequency (%)
0 23450
89.5%
1 2758
 
10.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23450
89.5%
1 2758
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23450
89.5%
1 2758
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23450
89.5%
1 2758
 
10.5%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25106 
1
 
1102

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25106
95.8%
1 1102
 
4.2%

Length

2025-05-15T14:19:02.706158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.743806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25106
95.8%
1 1102
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25106
95.8%
1 1102
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25106
95.8%
1 1102
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25106
95.8%
1 1102
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25106
95.8%
1 1102
 
4.2%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23876 
1
 
2332

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Length

2025-05-15T14:19:02.786945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.823775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23876
91.1%
1 2332
 
8.9%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22590 
1
3618 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22590
86.2%
1 3618
 
13.8%

Length

2025-05-15T14:19:02.870145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.907487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22590
86.2%
1 3618
 
13.8%

Most occurring characters

ValueCountFrequency (%)
0 22590
86.2%
1 3618
 
13.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22590
86.2%
1 3618
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22590
86.2%
1 3618
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22590
86.2%
1 3618
 
13.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22943 
1
3265 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22943
87.5%
1 3265
 
12.5%

Length

2025-05-15T14:19:02.952613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:02.991236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22943
87.5%
1 3265
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0 22943
87.5%
1 3265
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22943
87.5%
1 3265
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22943
87.5%
1 3265
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22943
87.5%
1 3265
 
12.5%

Grid Production ReactivePower StdDev [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21260 
1
4948 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21260
81.1%
1 4948
 
18.9%

Length

2025-05-15T14:19:03.037189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.074246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21260
81.1%
1 4948
 
18.9%

Most occurring characters

ValueCountFrequency (%)
0 21260
81.1%
1 4948
 
18.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21260
81.1%
1 4948
 
18.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21260
81.1%
1 4948
 
18.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21260
81.1%
1 4948
 
18.9%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25491 
1
 
717

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25491
97.3%
1 717
 
2.7%

Length

2025-05-15T14:19:03.121123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.157191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25491
97.3%
1 717
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25491
97.3%
1 717
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25491
97.3%
1 717
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25491
97.3%
1 717
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25491
97.3%
1 717
 
2.7%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25229 
1
 
979

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25229
96.3%
1 979
 
3.7%

Length

2025-05-15T14:19:03.199994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.238215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25229
96.3%
1 979
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25229
96.3%
1 979
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25229
96.3%
1 979
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25229
96.3%
1 979
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25229
96.3%
1 979
 
3.7%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25225 
1
 
983

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25225
96.2%
1 983
 
3.8%

Length

2025-05-15T14:19:03.280781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.316868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25225
96.2%
1 983
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25225
96.2%
1 983
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25225
96.2%
1 983
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25225
96.2%
1 983
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25225
96.2%
1 983
 
3.8%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25361 
1
 
847

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25361
96.8%
1 847
 
3.2%

Length

2025-05-15T14:19:03.361557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.399675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25361
96.8%
1 847
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25361
96.8%
1 847
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25361
96.8%
1 847
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25361
96.8%
1 847
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25361
96.8%
1 847
 
3.2%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.443271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.478830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.518771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.552868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.594905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.628674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.668406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.704808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.744645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.778414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.820104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.853968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.893786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:03.929877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:03.969731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.003624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26176 
1
 
32

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Length

2025-05-15T14:19:04.046821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.083180image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26176
99.9%
1 32
 
0.1%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-15T14:19:04.126238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.164014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:04.206657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.240867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-15T14:19:04.282739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.319230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-15T14:19:04.362299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.400491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25841 
1
 
367

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25841
98.6%
1 367
 
1.4%

Length

2025-05-15T14:19:04.443848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.480113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25841
98.6%
1 367
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 25841
98.6%
1 367
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25841
98.6%
1 367
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25841
98.6%
1 367
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25841
98.6%
1 367
 
1.4%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25158 
1
 
1050

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Length

2025-05-15T14:19:04.524500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.560851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25238 
1
 
970

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Length

2025-05-15T14:19:04.603992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.641912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23862 
1
 
2346

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Length

2025-05-15T14:19:04.685160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.722483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24596 
1
 
1612

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Length

2025-05-15T14:19:04.768978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.805386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24596
93.8%
1 1612
 
6.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22116 
1
4092 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22116
84.4%
1 4092
 
15.6%

Length

2025-05-15T14:19:04.848281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:04.886993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22116
84.4%
1 4092
 
15.6%

Most occurring characters

ValueCountFrequency (%)
0 22116
84.4%
1 4092
 
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22116
84.4%
1 4092
 
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22116
84.4%
1 4092
 
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22116
84.4%
1 4092
 
15.6%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24727 
1
 
1481

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24727
94.3%
1 1481
 
5.7%

Length

2025-05-15T14:19:05.087606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.123509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24727
94.3%
1 1481
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24727
94.3%
1 1481
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24727
94.3%
1 1481
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24727
94.3%
1 1481
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24727
94.3%
1 1481
 
5.7%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:05.167726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.201605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23726 
1
2482 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23726
90.5%
1 2482
 
9.5%

Length

2025-05-15T14:19:05.241284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.279809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23726
90.5%
1 2482
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23726
90.5%
1 2482
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23726
90.5%
1 2482
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23726
90.5%
1 2482
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23726
90.5%
1 2482
 
9.5%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23821 
1
2387 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23821
90.9%
1 2387
 
9.1%

Length

2025-05-15T14:19:05.324557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.361639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23821
90.9%
1 2387
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23821
90.9%
1 2387
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23821
90.9%
1 2387
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23821
90.9%
1 2387
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23821
90.9%
1 2387
 
9.1%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23970 
1
 
2238

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23970
91.5%
1 2238
 
8.5%

Length

2025-05-15T14:19:05.408177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.445107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23970
91.5%
1 2238
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23970
91.5%
1 2238
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23970
91.5%
1 2238
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23970
91.5%
1 2238
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23970
91.5%
1 2238
 
8.5%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22986 
1
3222 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22986
87.7%
1 3222
 
12.3%

Length

2025-05-15T14:19:05.489971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.528770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22986
87.7%
1 3222
 
12.3%

Most occurring characters

ValueCountFrequency (%)
0 22986
87.7%
1 3222
 
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22986
87.7%
1 3222
 
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22986
87.7%
1 3222
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22986
87.7%
1 3222
 
12.3%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25542 
1
 
666

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Length

2025-05-15T14:19:05.573400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.609569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25542
97.5%
1 666
 
2.5%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25287 
1
 
921

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25287
96.5%
1 921
 
3.5%

Length

2025-05-15T14:19:05.654138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.690755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25287
96.5%
1 921
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25287
96.5%
1 921
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25287
96.5%
1 921
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25287
96.5%
1 921
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25287
96.5%
1 921
 
3.5%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25503 
1
 
705

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25503
97.3%
1 705
 
2.7%

Length

2025-05-15T14:19:05.735519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.771676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25503
97.3%
1 705
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25503
97.3%
1 705
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25503
97.3%
1 705
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25503
97.3%
1 705
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25503
97.3%
1 705
 
2.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23077 
1
3131 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23077
88.1%
1 3131
 
11.9%

Length

2025-05-15T14:19:05.814623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.854020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23077
88.1%
1 3131
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23077
88.1%
1 3131
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23077
88.1%
1 3131
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23077
88.1%
1 3131
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23077
88.1%
1 3131
 
11.9%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:05.899518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:05.933722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26181 
1
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26181
99.9%
1 27
 
0.1%

Length

2025-05-15T14:19:05.975536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.011836image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26181
99.9%
1 27
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26181
99.9%
1 27
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26181
99.9%
1 27
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26181
99.9%
1 27
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26181
99.9%
1 27
 
0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26148 
1
 
60

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26148
99.8%
1 60
 
0.2%

Length

2025-05-15T14:19:06.055143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.093194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26148
99.8%
1 60
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26148
99.8%
1 60
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26148
99.8%
1 60
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26148
99.8%
1 60
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26148
99.8%
1 60
 
0.2%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26135 
1
 
73

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Length

2025-05-15T14:19:06.135964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.172183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26051 
1
 
157

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26051
99.4%
1 157
 
0.6%

Length

2025-05-15T14:19:06.216800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.253040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26051
99.4%
1 157
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26051
99.4%
1 157
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26051
99.4%
1 157
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26051
99.4%
1 157
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26051
99.4%
1 157
 
0.6%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25394 
1
 
814

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25394
96.9%
1 814
 
3.1%

Length

2025-05-15T14:19:06.295689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.333718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25394
96.9%
1 814
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25394
96.9%
1 814
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25394
96.9%
1 814
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25394
96.9%
1 814
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25394
96.9%
1 814
 
3.1%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24282 
1
 
1926

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24282
92.7%
1 1926
 
7.3%

Length

2025-05-15T14:19:06.377211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.413357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24282
92.7%
1 1926
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0 24282
92.7%
1 1926
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24282
92.7%
1 1926
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24282
92.7%
1 1926
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24282
92.7%
1 1926
 
7.3%

HourCounters Average Yaw Avg. [h]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23701 
1
2507 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23701
90.4%
1 2507
 
9.6%

Length

2025-05-15T14:19:06.458123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.495392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23701
90.4%
1 2507
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23701
90.4%
1 2507
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23701
90.4%
1 2507
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23701
90.4%
1 2507
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23701
90.4%
1 2507
 
9.6%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26160 
1
 
48

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26160
99.8%
1 48
 
0.2%

Length

2025-05-15T14:19:06.540141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.578791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26160
99.8%
1 48
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26160
99.8%
1 48
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26160
99.8%
1 48
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26160
99.8%
1 48
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26160
99.8%
1 48
 
0.2%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26075 
1
 
133

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26075
99.5%
1 133
 
0.5%

Length

2025-05-15T14:19:06.621871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.658148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26075
99.5%
1 133
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26075
99.5%
1 133
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26075
99.5%
1 133
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26075
99.5%
1 133
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26075
99.5%
1 133
 
0.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24528 
1
 
1680

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24528
93.6%
1 1680
 
6.4%

Length

2025-05-15T14:19:06.703503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.740504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24528
93.6%
1 1680
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24528
93.6%
1 1680
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24528
93.6%
1 1680
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24528
93.6%
1 1680
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24528
93.6%
1 1680
 
6.4%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26049 
1
 
159

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26049
99.4%
1 159
 
0.6%

Length

2025-05-15T14:19:06.783409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.821668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26049
99.4%
1 159
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26049
99.4%
1 159
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26049
99.4%
1 159
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26049
99.4%
1 159
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26049
99.4%
1 159
 
0.6%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:06.864909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.899266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:06.941011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:06.975227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.015153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.051513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.092721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.126931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.168669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.202824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.242674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.278576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.318516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.352479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.394566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.428392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.468407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.504364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.544475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.578476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:07.620297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.654353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24726 
1
 
1482

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Length

2025-05-15T14:19:07.694985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.733159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24726
94.3%
1 1482
 
5.7%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25544 
1
 
664

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25544
97.5%
1 664
 
2.5%

Length

2025-05-15T14:19:07.776386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:07.812887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25544
97.5%
1 664
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25544
97.5%
1 664
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25544
97.5%
1 664
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25544
97.5%
1 664
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25544
97.5%
1 664
 
2.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25078 
1
 
1130

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Length

2025-05-15T14:19:08.016044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.052546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25078
95.7%
1 1130
 
4.3%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25244 
1
 
964

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25244
96.3%
1 964
 
3.7%

Length

2025-05-15T14:19:08.095593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.133375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25244
96.3%
1 964
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25244
96.3%
1 964
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25244
96.3%
1 964
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25244
96.3%
1 964
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25244
96.3%
1 964
 
3.7%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24613 
1
 
1595

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24613
93.9%
1 1595
 
6.1%

Length

2025-05-15T14:19:08.175963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.212789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24613
93.9%
1 1595
 
6.1%

Most occurring characters

ValueCountFrequency (%)
0 24613
93.9%
1 1595
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24613
93.9%
1 1595
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24613
93.9%
1 1595
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24613
93.9%
1 1595
 
6.1%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23883 
1
 
2325

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23883
91.1%
1 2325
 
8.9%

Length

2025-05-15T14:19:08.257182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.294074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23883
91.1%
1 2325
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23883
91.1%
1 2325
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23883
91.1%
1 2325
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23883
91.1%
1 2325
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23883
91.1%
1 2325
 
8.9%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23955 
1
 
2253

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23955
91.4%
1 2253
 
8.6%

Length

2025-05-15T14:19:08.338708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.377977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23955
91.4%
1 2253
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23955
91.4%
1 2253
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23955
91.4%
1 2253
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23955
91.4%
1 2253
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23955
91.4%
1 2253
 
8.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22188 
1
4020 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22188
84.7%
1 4020
 
15.3%

Length

2025-05-15T14:19:08.423177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.459827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22188
84.7%
1 4020
 
15.3%

Most occurring characters

ValueCountFrequency (%)
0 22188
84.7%
1 4020
 
15.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22188
84.7%
1 4020
 
15.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22188
84.7%
1 4020
 
15.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22188
84.7%
1 4020
 
15.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:08.506475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.540866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:08.580904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.617239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26205 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Length

2025-05-15T14:19:08.657546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.694017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26058 
1
 
150

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26058
99.4%
1 150
 
0.6%

Length

2025-05-15T14:19:08.739472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.775849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26058
99.4%
1 150
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26058
99.4%
1 150
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26058
99.4%
1 150
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26058
99.4%
1 150
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26058
99.4%
1 150
 
0.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26074 
1
 
134

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Length

2025-05-15T14:19:08.820230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.856502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26074
99.5%
1 134
 
0.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:08.899745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:08.933708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:19:08.975568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:09.009537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26015 
1
 
193

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Length

2025-05-15T14:19:09.051074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:19:09.087747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Correlations

2025-05-15T14:19:09.214895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0240.0030.0000.0070.0040.0040.0050.0040.0000.0200.0020.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.000
Active power limit [W]0.0001.0000.3090.0000.0000.0290.0000.0090.0530.0000.0500.0160.0420.0480.0840.0540.0110.0100.0120.0000.0000.0000.0000.0000.0000.0000.0110.0120.0000.0070.0000.0000.0050.0120.0150.0340.0210.0000.0000.0000.0430.0040.0030.0110.0000.0000.0000.0000.0000.0040.0340.0060.0270.0560.0350.0610.0460.0000.0000.0000.0040.0060.0000.0070.0100.0050.0240.2010.2820.0070.0380.4210.7990.1880.2160.2780.0820.0000.0000.0100.3090.3090.0690.0000.0000.0660.0000.0170.0000.0380.0350.0140.0060.0280.0290.0110.0000.000
Active power limit source0.0000.3091.0000.0000.0000.0240.0000.0000.0000.0000.0230.0220.0320.0000.0000.0000.0000.0150.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0090.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0580.1080.0000.0250.1610.3370.0990.1080.1460.0280.0000.0000.0000.8750.8750.0300.0000.0000.0280.0000.0000.0000.0150.0000.0000.0000.0180.0000.0000.0000.000
Ambient Temp. Avg. [°C]0.0000.0000.0001.0000.0200.0040.0210.0010.0130.0000.0090.0110.0080.0130.0000.0160.0340.0100.0520.0000.0020.0000.0000.0110.0000.0120.0140.0100.0000.0000.0060.0110.0030.0090.0160.0200.0000.0310.0360.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0040.0000.0140.0000.0080.0060.0000.0000.0000.0000.0030.0000.0280.0000.0130.0000.0130.0070.0170.0200.0070.0000.0120.0000.0130.0120.0000.0080.0680.0000.0000.0090.0130.0030.0090.0000.0120.0000.0110.0000.0100.0050.0180.0000.0200.0050.000
Ambient WindDir Absolute Avg. [°]0.0000.0000.0000.0201.0000.1640.0000.0080.0000.0070.0180.0430.0140.0090.0040.0020.0100.0000.0110.0000.0020.0000.0000.0080.0100.0000.0300.0110.0000.0000.0000.0150.0000.0140.0380.0180.0050.0090.0060.0040.0230.0250.0210.0280.0000.0120.0000.0000.0090.0200.0140.0090.0000.0390.0200.0230.0000.0000.0050.0000.0050.0230.0120.0130.0060.0000.0000.0200.0210.0110.0290.0000.0000.0210.0000.0000.0160.0310.0000.0000.0000.0000.0440.0000.0090.0480.0050.0160.0170.0220.0000.0220.0310.0130.0000.0180.0000.000
Ambient WindDir Relative Avg. [°]0.0000.0290.0240.0040.1641.0000.0120.0250.0000.0000.1100.1290.0640.0440.0000.0210.0000.0130.0090.0000.0000.0040.0080.0150.0410.0090.0690.0060.0210.0000.0000.0090.0010.0880.1130.0700.0550.0000.0000.0080.0610.0000.0000.0000.0000.0180.0000.0000.0000.0030.0000.0000.0050.1090.0430.0620.0320.0000.0000.0070.0000.0000.0000.0160.0150.0000.0000.0940.0870.0130.0810.0690.0250.0980.0630.0910.0180.0120.0150.0000.0240.0240.1110.0070.0000.1350.0120.0390.0080.0730.0050.0980.0900.0560.0480.0520.0260.014
Ambient WindSpeed Avg. [m/s]0.0000.0000.0000.0210.0000.0121.0000.1220.0950.0150.1270.0680.0460.0610.0000.0000.0080.0030.0100.0060.0800.0490.0610.0540.0450.0430.0040.0000.0150.0000.0300.0290.0300.1080.0760.0730.0470.0000.0100.0400.0420.1980.2010.1900.0000.2240.0850.0930.0710.2010.0790.0830.0680.0390.0430.0340.0240.0000.0020.0000.0230.0340.0280.0040.0000.0000.0040.0000.0000.0160.0500.0000.0000.0000.0000.0000.0510.0210.0000.0090.0000.0000.0510.0960.0980.0370.0000.0050.1930.0290.0000.1030.0670.0780.0430.0000.0000.002
Ambient WindSpeed Max. [m/s]0.0000.0090.0000.0010.0080.0250.1221.0000.0260.0530.0510.0550.0380.0250.0000.0000.0000.0020.0050.0000.0290.0290.0310.0320.0140.0300.0000.0000.0000.0000.0000.0140.0120.0470.0550.0290.0310.0000.0140.0250.0230.0990.0840.0850.0000.0940.0950.0510.0820.0790.0870.0460.0790.0270.0380.0270.0210.0000.0000.0040.0240.0170.0140.0190.0000.0000.0130.0000.0000.0160.0290.0000.0000.0000.0000.0000.0460.0290.0000.0000.0000.0000.0280.0460.0410.0250.0000.0000.0780.0140.0000.0350.0560.0310.0250.0000.0000.000
Ambient WindSpeed Min. [m/s]0.0000.0530.0000.0130.0000.0000.0950.0261.0000.0430.1030.0200.1220.0940.0000.0100.0000.0110.0100.0000.0300.0280.0450.0300.0350.0300.0070.0000.0000.0000.0200.0180.0190.0680.0610.1100.0550.0140.0190.0310.0520.0680.0720.0750.0030.0560.0360.1010.0340.0700.0530.0870.0450.0750.0720.0680.0600.0000.0000.0000.0160.0080.0070.0250.0100.0040.0060.0140.0210.0660.0670.0290.0580.0100.0000.0140.0360.0220.0000.0000.0000.0000.0470.0520.0730.0380.0090.0620.0720.0500.0000.0600.0480.0920.0320.0120.0000.000
Ambient WindSpeed StdDev [m/s]0.0000.0000.0000.0000.0070.0000.0150.0530.0431.0000.0540.0080.0460.0820.0000.0000.0110.0000.0000.0100.0100.0080.0100.0050.0000.0000.0000.0000.0000.0060.0190.0140.0120.0260.0390.0120.0730.0000.0000.0210.0260.0390.0490.0480.0050.0400.0260.0450.1260.0400.0390.0340.1200.0310.0270.0300.0260.0000.0000.0070.0360.0240.0200.0070.0000.0110.0000.0000.0030.0120.0250.0000.0000.0000.0000.0000.0000.0570.0000.0030.0000.0000.0290.0240.0190.0240.0120.0190.0420.0020.0000.0210.0330.0140.0490.0000.0000.000
Blades PitchAngle Avg. [°]0.0000.0500.0230.0090.0180.1100.1270.0510.1030.0541.0000.2600.4330.4640.0040.0090.0000.0220.0250.0000.0510.0470.0380.0920.1520.0480.0570.0230.0270.0050.0240.0240.0220.2390.2240.2500.2280.0220.0490.0460.3070.1550.1580.1700.0000.1930.1830.2070.2570.1890.1710.1580.2350.4250.2970.2420.2500.0120.0110.0000.0560.0300.0300.0380.0130.0130.0200.1790.1520.1630.3950.0870.0520.1810.0740.1220.1100.0820.0000.0250.0230.0230.3720.0760.2470.3470.0830.2630.1920.3030.0220.2580.2040.2090.1830.0390.0680.043
Blades PitchAngle Max. [°]0.0000.0160.0220.0110.0430.1290.0680.0550.0200.0080.2601.0000.1310.0950.0000.0000.0000.0240.0120.0060.0340.0220.0000.0660.0640.0440.0630.0020.0140.0240.0000.0100.0050.1210.2470.0670.0730.0000.0110.0110.2480.1080.1070.1130.0030.1450.1550.1120.1730.1280.1380.0720.1190.1930.1520.0910.0670.0000.0000.0000.0210.0170.0000.0210.0210.0170.0080.1090.0980.0110.1840.0410.0200.1080.0430.0670.1750.0400.0000.0140.0220.0220.2430.0000.1010.2530.0170.0730.1310.1520.0000.1140.2240.0690.0640.0410.0840.021
Blades PitchAngle Min. [°]0.0000.0420.0320.0080.0140.0640.0460.0380.1220.0460.4330.1311.0000.5550.0000.0100.0000.0070.0160.0000.0570.0600.0550.0960.1170.0430.0000.0280.0320.0110.0170.0110.0070.2170.1330.3540.2300.0310.0360.0280.3850.1140.1180.1260.0090.1590.1260.1680.1820.1550.1120.1410.1950.6380.4710.3580.4070.0060.0000.0000.0400.0260.0290.0300.0130.0210.0160.1520.1150.3100.5430.0540.0400.1550.0390.0930.1230.0450.0060.0310.0320.0320.4430.1730.2790.4080.1910.4630.1600.4570.0560.2230.1160.2870.1790.0260.0430.073
Blades PitchAngle StdDev [°]0.0000.0480.0000.0130.0090.0440.0610.0250.0940.0820.4640.0950.5551.0000.0080.0160.0070.0150.0170.0150.0170.0190.0310.0420.0810.0110.0210.0310.0170.0000.0110.0090.0000.1740.1380.2640.3920.0180.0250.0160.3180.1150.1210.1210.0000.1730.1480.2500.2310.1590.1120.1850.2510.5000.3710.2840.4130.0060.0090.0070.0330.0240.0160.0300.0180.0210.0260.1370.1150.2510.4320.0630.0440.1360.0610.0780.0910.0990.0000.0150.0000.0000.3370.1440.2700.3150.1590.5060.1590.3480.0710.1880.1250.2050.3140.0170.0630.101
Controller Ground Temp. Avg. [°C]0.0000.0840.0000.0000.0040.0000.0000.0000.0000.0000.0040.0000.0000.0081.0000.0080.0010.0000.0200.0170.0090.0000.0000.0170.0000.0110.0110.0090.0050.0130.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0070.0000.0000.0080.0000.0000.0040.0040.0050.0000.0000.0050.0000.0000.0020.0050.0060.0080.0080.0090.0080.0200.0140.0000.0000.0000.0000.0300.0440.0180.0070.0650.0920.0260.0360.0390.0090.0000.0170.0120.0000.0000.0000.0110.0000.0080.0080.0000.0000.0060.0000.0000.0080.0000.0080.0000.0030.000
Controller Hub Temp. Avg. [°C]0.0000.0540.0000.0160.0020.0210.0000.0000.0100.0000.0090.0000.0100.0160.0081.0000.0150.0150.0040.0000.0000.0030.0110.0000.0140.0040.0240.0070.0000.0050.0050.0000.0000.0090.0220.0190.0380.0120.0090.0060.0130.0270.0250.0290.0000.0080.0030.0110.0160.0300.0190.0330.0150.0310.0000.0160.0310.0040.0000.0000.0000.0000.0000.0110.0000.0030.0000.0300.0410.0400.0380.0300.0530.0300.0000.0210.0000.0070.0000.0000.0000.0000.0340.0290.0220.0310.0000.0210.0330.0200.0040.0100.0120.0030.0240.0710.0000.000
Controller Top Temp. Avg. [°C]0.0000.0110.0000.0340.0100.0000.0080.0000.0000.0110.0000.0000.0000.0070.0010.0151.0000.0040.0420.0150.0000.0000.0000.0100.0000.0170.0090.0220.0000.0060.0060.0000.0040.0000.0000.0100.0000.0000.0000.0000.0040.0000.0000.0040.0000.0110.0070.0250.0000.0060.0000.0000.0000.0090.0080.0140.0000.0000.0000.0000.0000.0000.0140.0160.0170.0520.0310.0220.0130.0130.0100.0200.0000.0220.0200.0350.0110.0000.0000.0740.0000.0000.0000.0120.0110.0050.0140.0000.0070.0120.0000.0030.0000.0070.0030.0040.0000.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0100.0150.0100.0000.0130.0030.0020.0110.0000.0220.0240.0070.0150.0000.0150.0041.0000.0320.0180.0170.0180.0000.0280.0340.0000.0170.0100.0000.0130.0290.0430.0290.0250.0180.0000.0380.0000.0410.0230.0330.0290.0330.0330.0070.0060.0230.0130.0000.0210.0380.0270.0100.0000.0050.0000.0080.0000.0040.0000.0240.0130.0170.0140.0350.0330.0290.0000.0000.0380.0000.0000.0180.0000.0000.0070.0000.0070.0000.0110.0150.0150.0320.0460.0070.0360.0150.0160.0160.0000.0140.0300.0130.0050.0390.0200.0170.020
Controller VCP Temp. Avg. [°C]0.0000.0120.0000.0520.0110.0090.0100.0050.0100.0000.0250.0120.0160.0170.0200.0040.0420.0321.0000.0030.0160.0130.0070.0160.0240.0160.0250.0610.0270.0190.0000.0000.0000.0220.0090.0220.0180.0840.0580.0000.0150.0000.0000.0030.0000.0000.0060.0000.0050.0000.0000.0000.0000.0050.0110.0100.0160.0000.0000.0000.0000.0000.0040.0280.0120.0530.0130.0150.0060.0000.0210.0250.0200.0150.0120.0400.0230.0000.0000.1200.0000.0000.0160.0000.0000.0120.0170.0210.0000.0230.0130.0100.0120.0220.0190.0000.0110.000
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0040.0000.0000.0000.0060.0000.0000.0100.0000.0060.0000.0150.0170.0000.0150.0180.0031.0000.0410.0410.0320.0300.0380.0250.0000.0360.0300.3130.0540.0600.0700.0370.0090.0180.0150.0090.0420.1560.0060.0200.0210.0200.0000.0000.0000.0000.0180.0110.0000.0090.0000.0000.0000.0150.0180.0000.0000.0000.2150.2690.2590.0170.0190.0000.0170.0000.0010.0000.0000.0010.0000.0000.0110.0000.0130.0110.0130.0000.0040.0040.0000.0150.0060.0000.0090.0190.0000.0070.0120.0300.0130.0360.0000.0030.0000.010
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0000.0020.0020.0000.0800.0290.0300.0100.0510.0340.0570.0170.0090.0000.0000.0170.0160.0411.0000.2920.2030.2340.1310.2610.0250.0190.0460.0410.1190.1090.1190.1490.0580.0790.0790.0200.0370.0570.0560.0660.0610.0610.0000.0680.0860.0370.0500.0660.0690.0220.0460.0350.0440.0430.0320.0120.0080.0040.0600.0690.0620.0060.0000.0100.0000.0460.0310.0130.0450.0000.0000.0470.0000.0140.0340.0100.0050.0000.0000.0000.0690.0650.0000.0620.0090.0030.0720.0450.0060.1280.0660.0870.0830.0000.0000.000
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0000.0000.0000.0040.0490.0290.0280.0080.0470.0220.0600.0190.0000.0030.0000.0180.0130.0410.2921.0000.1360.2400.1820.2300.0140.0140.0450.0250.1020.0940.0950.1430.0620.1030.0820.0320.0440.0560.0610.0610.0610.0570.0000.0550.0630.0380.0370.0640.0560.0310.0420.0490.0420.0580.0270.0120.0110.0140.0680.0640.0770.0000.0000.0070.0000.0480.0340.0160.0510.0000.0000.0480.0000.0160.0190.0000.0120.0040.0000.0000.0810.0630.0080.0790.0060.0180.0610.0390.0060.1460.0600.1140.0860.0140.0060.007
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0000.0000.0000.0000.0080.0610.0310.0450.0100.0380.0000.0550.0310.0000.0110.0000.0000.0070.0320.2030.1361.0000.1890.1560.2110.0500.0140.0440.0340.0480.0410.0510.1420.0440.0980.1130.0180.0150.0440.0380.0880.0860.0750.0040.0760.0800.0430.0720.0820.0800.0480.0710.0360.0490.0290.0200.0050.0000.0070.0560.0470.0520.0000.0070.0160.0000.0740.0460.0460.0280.0000.0000.0740.0000.0330.0000.0220.0000.0000.0000.0000.0480.0520.0420.0480.0170.0020.0890.0360.0000.1570.0610.0880.0640.0070.0000.006
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0000.0110.0080.0150.0540.0320.0300.0050.0920.0660.0960.0420.0170.0000.0100.0280.0160.0300.2340.2400.1891.0000.2150.2470.0180.0430.0540.0450.0920.0930.0760.1660.0590.1530.0880.0270.0540.0450.0990.0390.0350.0380.0000.0530.0730.0460.0590.0440.0680.0210.0530.0740.0630.0610.0520.0000.0000.0000.0540.0490.0580.0090.0150.0120.0000.0420.0270.0340.0880.0000.0000.0430.0000.0150.0460.0080.0100.0030.0000.0000.1060.0700.0100.1020.0000.0280.0470.0650.0000.1700.0700.1430.0910.0200.0000.000
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0000.0000.0000.0100.0410.0450.0140.0350.0000.1520.0640.1170.0810.0000.0140.0000.0340.0240.0380.1310.1820.1560.2151.0000.1460.0320.0400.0520.0270.0800.0830.0750.1920.1070.1890.1130.0320.0710.0340.0960.0390.0350.0390.0010.0420.0470.0530.0480.0390.0430.0350.0510.1140.0860.0910.0550.0000.0000.0000.0570.0480.0470.0270.0080.0090.0160.0580.0370.0660.1420.0000.0000.0580.0000.0170.0570.0160.0070.0000.0000.0000.1430.0610.0200.1360.0000.0500.0420.0800.0070.2080.0970.1760.0840.0230.0000.019
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0000.0120.0000.0090.0430.0300.0300.0000.0480.0440.0430.0110.0110.0040.0170.0000.0160.0250.2610.2300.2110.2470.1461.0000.0490.0180.0460.0350.0900.0860.0940.1610.0820.0720.0940.0470.0390.0280.0340.0430.0420.0360.0000.0370.0680.0270.0410.0370.0670.0250.0430.0230.0330.0360.0260.0000.0000.0040.0410.0340.0410.0060.0100.0000.0000.0210.0210.0000.0310.0190.0000.0210.0250.0200.0210.0000.0250.0000.0000.0000.0550.0090.0000.0500.0040.0000.0340.0320.0000.1670.0890.0790.0930.0090.0000.000
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0110.0000.0140.0300.0690.0040.0000.0070.0000.0570.0630.0000.0210.0110.0240.0090.0170.0250.0000.0250.0140.0500.0180.0320.0491.0000.0220.0140.0040.0020.0000.0080.0490.0760.0130.0630.0070.0000.0180.0240.0310.0340.0310.0120.0250.0430.0340.0520.0260.0490.0490.0520.0280.0000.0050.0320.0050.0000.0000.0040.0000.0040.0030.0000.0000.0000.0890.0690.0110.0160.0360.0150.0860.0300.0660.0420.0230.0000.0320.0000.0000.0340.0000.0170.0430.0180.0000.0250.0360.0140.0400.0750.0000.0550.0470.0660.019
Generator Bearing Temp. Avg. [°C]0.0000.0120.0000.0100.0110.0060.0000.0000.0000.0000.0230.0020.0280.0310.0090.0070.0220.0100.0610.0360.0190.0140.0140.0430.0400.0180.0221.0000.0570.0280.0300.0330.0230.0100.0000.0300.0290.0160.0460.0090.0250.0000.0000.0000.0060.0160.0170.0350.0200.0100.0140.0190.0130.0080.0100.0020.0220.0000.0000.0090.0170.0150.0150.0180.0510.0450.0240.0040.0000.0230.0410.0060.0090.0070.0000.0170.0160.0000.0000.0240.0000.0000.0120.0200.0180.0120.0000.0370.0120.0070.0000.0080.0000.0250.0190.0000.0000.009
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0210.0150.0000.0000.0000.0270.0140.0320.0170.0050.0000.0000.0000.0270.0300.0460.0450.0440.0540.0520.0460.0140.0571.0000.0420.0340.0380.0320.0530.0360.0440.0370.0300.0310.0000.0360.0130.0180.0180.0000.0180.0190.0050.0160.0140.0140.0140.0030.0330.0380.0280.0260.0000.0010.0000.0240.0250.0350.0250.0130.0130.0000.0000.0000.0000.0420.0000.0000.0000.0000.0000.0170.0160.0110.0130.0000.0000.0470.0040.0080.0480.0000.0330.0160.0270.0090.0610.0360.0330.0370.0290.0110.011
Generator CoolingWater Temp. Avg. [°C]0.0000.0070.0000.0000.0000.0000.0000.0000.0000.0060.0050.0240.0110.0000.0130.0050.0060.0130.0190.3130.0410.0250.0340.0450.0270.0350.0040.0280.0421.0000.0350.0340.0380.0490.0190.0320.0190.0020.0340.0910.0210.0000.0000.0000.0000.0000.0120.0050.0100.0000.0180.0050.0000.0060.0080.0130.0020.0000.0000.0000.1710.1720.1640.0170.0000.0000.0080.0000.0000.0040.0190.0040.0050.0000.0050.0000.0530.0180.0040.0000.0000.0000.0260.0000.0100.0280.0190.0000.0000.0000.0000.0430.0220.0380.0100.0000.0080.000
Generator Phase1 Temp. Avg. [°C]0.0000.0000.0000.0060.0000.0000.0300.0000.0200.0190.0240.0000.0170.0110.0000.0050.0060.0290.0000.0540.1190.1020.0480.0920.0800.0900.0020.0300.0340.0351.0000.4670.4380.0440.0380.0270.0380.0200.0520.0830.0430.0830.0920.0870.0000.0480.0290.0300.0400.0690.0710.0400.0430.0250.0340.0300.0080.0000.0000.0000.0910.0740.0790.0000.0090.0280.0150.0000.0000.0120.0200.0000.0000.0000.0000.0000.0180.0120.0140.0000.0000.0000.0510.0000.0230.0470.0370.0000.0610.0000.0090.0410.0270.0380.0200.0160.0360.011
Generator Phase2 Temp. Avg. [°C]0.0000.0000.0000.0110.0150.0090.0290.0140.0180.0140.0240.0100.0110.0090.0000.0000.0000.0430.0000.0600.1090.0940.0410.0930.0830.0860.0000.0330.0380.0340.4671.0000.4760.0480.0440.0190.0420.0060.0660.0800.0330.0890.0910.0850.0000.0490.0350.0330.0510.0680.0650.0460.0490.0170.0300.0360.0130.0000.0000.0000.0730.0820.0970.0160.0390.0170.0090.0000.0000.0130.0050.0000.0000.0000.0000.0000.0270.0190.0150.0000.0000.0000.0340.0000.0180.0370.0280.0050.0650.0000.0000.0470.0300.0350.0320.0280.0300.007
Generator Phase3 Temp. Avg. [°C]0.0000.0050.0000.0030.0000.0010.0300.0120.0190.0120.0220.0050.0070.0000.0000.0000.0040.0290.0000.0700.1190.0950.0510.0760.0750.0940.0080.0230.0320.0380.4380.4761.0000.0420.0450.0140.0370.0140.0480.0760.0230.0670.0730.0760.0030.0250.0210.0210.0400.0470.0560.0420.0340.0120.0210.0270.0000.0040.0020.0090.0800.0740.0770.0130.0130.0260.0180.0000.0000.0120.0040.0000.0000.0000.0000.0000.0220.0120.0270.0120.0000.0000.0310.0050.0110.0350.0400.0000.0460.0070.0110.0510.0280.0260.0350.0220.0260.006
Generator RPM Avg. [RPM]0.0000.0120.0000.0090.0140.0880.1080.0470.0680.0260.2390.1210.2170.1740.0000.0090.0000.0250.0220.0370.1490.1430.1420.1660.1920.1610.0490.0100.0530.0490.0440.0480.0421.0000.3770.3590.4460.0240.0450.0150.1990.1400.1390.1420.0000.1430.1650.1440.1780.1510.1520.1030.1690.2040.1280.1580.1080.0080.0170.0000.0580.0500.0450.0220.0130.0090.0090.1370.1160.0440.2130.0350.0150.1390.0300.0630.0260.0580.0120.0190.0000.0000.2800.0460.0870.2780.0210.1070.1540.1720.0250.7390.3520.3270.3940.0530.0170.057
Generator RPM Max. [RPM]0.0000.0150.0000.0160.0380.1130.0760.0550.0610.0390.2240.2470.1330.1380.0000.0220.0000.0180.0090.0090.0580.0620.0440.0590.1070.0820.0760.0000.0360.0190.0380.0440.0450.3771.0000.1340.2940.0170.0340.0340.1750.1250.1250.1280.0000.1260.1750.1420.1910.1290.1750.1060.1480.1810.1380.0920.0950.0000.0090.0020.0460.0330.0420.0310.0030.0000.0000.0980.0890.0690.1820.0380.0140.0970.0390.0570.0350.0560.0000.0100.0000.0000.1930.0030.1460.2110.0270.1190.1280.1220.0000.3240.7420.1160.2330.0600.0680.009
Generator RPM Min. [RPM]0.0000.0340.0210.0200.0180.0700.0730.0290.1100.0120.2500.0670.3540.2640.0000.0190.0100.0000.0220.0180.0790.1030.0980.1530.1890.0720.0130.0300.0440.0320.0270.0190.0140.3590.1341.0000.2590.0270.0500.0300.2830.1050.1030.1040.0000.1000.0740.1720.0830.1300.0680.1600.0940.3290.2220.2400.2010.0070.0150.0000.0450.0320.0380.0330.0090.0110.0000.1230.0900.2030.4060.0360.0350.1270.0160.0730.1170.0320.0030.0220.0210.0210.3760.1620.1350.3360.0290.2580.1290.2380.0610.3680.1260.7690.2130.0350.0270.084
Generator RPM StdDev [RPM]0.0000.0210.0000.0000.0050.0550.0470.0310.0550.0730.2280.0730.2300.3920.0000.0380.0000.0380.0180.0150.0790.0820.1130.0880.1130.0940.0630.0290.0370.0190.0380.0420.0370.4460.2940.2591.0000.0120.0340.0210.2650.1400.1390.1420.0000.1560.1650.2650.2290.1650.1520.2170.2510.2050.1450.1590.2340.0000.0000.0000.0430.0470.0370.0170.0000.0000.0000.1250.0980.0180.2170.0390.0110.1250.0320.0580.0430.1140.0000.0120.0000.0000.2700.0110.1460.2600.0050.2950.1590.1320.0560.4170.2600.2270.6960.0420.0730.096
Generator SlipRing Temp. Avg. [°C]0.0000.0000.0000.0310.0090.0000.0000.0000.0140.0000.0220.0000.0310.0180.0010.0120.0000.0000.0840.0090.0200.0320.0180.0270.0320.0470.0070.0160.0300.0020.0200.0060.0140.0240.0170.0270.0121.0000.0870.0000.0320.0250.0210.0250.0000.0270.0130.0140.0240.0280.0260.0120.0180.0320.0280.0200.0280.0040.0000.0000.0000.0160.0000.0490.0210.0000.0060.0000.0020.0050.0330.0110.0000.0000.0130.0000.0210.0160.0160.0810.0000.0000.0370.0260.0250.0380.0190.0300.0350.0410.0080.0230.0140.0190.0160.0200.0250.010
Grid Busbar Temp. Avg. [°C]0.0000.0000.0090.0360.0060.0000.0100.0140.0190.0000.0490.0110.0360.0250.0000.0090.0000.0410.0580.0420.0370.0440.0150.0540.0710.0390.0000.0460.0310.0340.0520.0660.0480.0450.0340.0500.0340.0871.0000.0180.0320.0170.0130.0170.0150.0000.0000.0230.0060.0120.0120.0130.0000.0370.0230.0330.0110.0000.0000.0000.0300.0400.0430.0460.0310.0380.0310.0040.0000.0160.0460.0000.0000.0000.0000.0070.0190.0100.0070.0720.0090.0090.0460.0140.0120.0410.0000.0310.0160.0230.0000.0420.0300.0470.0200.0250.0000.007
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0040.0080.0400.0250.0310.0210.0460.0110.0280.0160.0000.0060.0000.0230.0000.1560.0570.0560.0440.0450.0340.0280.0180.0090.0000.0910.0830.0800.0760.0150.0340.0300.0210.0000.0181.0000.0170.0900.1030.1030.0000.0570.0300.0400.0380.0820.0590.0500.0440.0310.0300.0420.0210.0000.0000.0000.3090.1820.2090.0130.0180.0000.0000.0290.0300.0210.0130.0000.0000.0290.0000.0000.0110.0000.0150.0000.0000.0000.0240.0460.0280.0300.0080.0100.0750.0070.0070.0050.0270.0390.0160.0090.0270.008
Grid Production CosPhi Avg.0.0000.0430.0170.0140.0230.0610.0420.0230.0520.0260.3070.2480.3850.3180.0070.0130.0040.0330.0150.0060.0560.0610.0380.0990.0960.0340.0240.0250.0360.0210.0430.0330.0230.1990.1750.2830.2650.0320.0320.0171.0000.1870.1870.2010.0060.2090.2200.2390.2480.2470.2410.2000.2370.4670.3350.2550.3000.0020.0010.0060.0390.0240.0250.0380.0000.0000.0000.1420.1270.0000.5020.0760.0430.1430.0720.1030.2240.1120.0000.0130.0170.0170.6190.0000.2110.5750.0590.4110.2480.3220.0730.2100.1460.2140.2090.0360.0810.085
Grid Production CurrentPhase1 Avg. [A]0.0040.0040.0000.0000.0250.0000.1980.0990.0680.0390.1550.1080.1140.1150.0000.0270.0000.0290.0000.0200.0660.0610.0880.0390.0390.0430.0310.0000.0130.0000.0830.0890.0670.1400.1250.1050.1400.0250.0170.0900.1871.0000.7940.7930.0000.5330.2430.2770.2740.6660.3180.3800.3190.2260.1380.1350.1470.0000.0130.0000.0620.0660.0630.0170.0000.0000.0030.1540.1380.0690.1330.0070.0000.1530.0110.0280.1480.1040.0180.0130.0000.0000.2780.2000.3290.2530.0000.0660.6350.1480.0000.1400.0960.0900.1230.0190.0600.007
Grid Production CurrentPhase2 Avg. [A]0.0240.0030.0000.0000.0210.0000.2010.0840.0720.0490.1580.1070.1180.1210.0000.0250.0000.0330.0000.0210.0610.0610.0860.0350.0350.0420.0340.0000.0180.0000.0920.0910.0730.1390.1250.1030.1390.0210.0130.1030.1870.7941.0000.7840.0000.5350.2450.2830.2790.6610.3160.3740.3190.2300.1380.1380.1490.0070.0120.0150.0740.0680.0750.0200.0000.0000.0020.1510.1350.0660.1350.0060.0000.1490.0100.0270.1430.1060.0160.0100.0000.0000.2650.1960.3350.2590.0000.0750.6230.1500.0000.1350.0950.0870.1220.0210.0710.007
Grid Production CurrentPhase3 Avg. [A]0.0030.0110.0000.0000.0280.0000.1900.0850.0750.0480.1700.1130.1260.1210.0080.0290.0040.0330.0030.0200.0610.0570.0750.0380.0390.0360.0310.0000.0180.0000.0870.0850.0760.1420.1280.1040.1420.0250.0170.1030.2010.7930.7841.0000.0000.5450.2570.2900.2940.6850.3430.3830.3420.2480.1490.1520.1570.0000.0000.0000.0720.0620.0720.0160.0000.0000.0010.1530.1350.0680.1520.0060.0060.1490.0150.0270.1170.1060.0210.0160.0000.0000.2980.1930.3470.2750.0000.0750.6580.1610.0000.1420.0980.0870.1240.0220.0630.013
Grid Production Frequency Avg. [Hz]0.0000.0000.0000.0000.0000.0000.0000.0000.0030.0050.0000.0030.0090.0000.0000.0000.0000.0070.0000.0000.0000.0000.0040.0000.0010.0000.0120.0060.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0150.0000.0060.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0110.0120.0100.0000.0000.0000.0050.0100.0000.0000.0000.0000.0010.0000.0000.0050.0090.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0070.0000.0000.0080.0000.0120.0000.0040.0000.0000.0000.0000.0000.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0070.0000.0000.0000.0120.0180.2240.0940.0560.0400.1930.1450.1590.1730.0000.0080.0110.0060.0000.0000.0680.0550.0760.0530.0420.0370.0250.0160.0180.0000.0480.0490.0250.1430.1260.1000.1560.0270.0000.0570.2090.5330.5350.5450.0001.0000.3460.4080.4090.6700.2990.2950.3650.1510.1410.0610.1160.0000.0050.0000.0350.0330.0370.0060.0090.0170.0230.1180.1110.0610.1980.0130.0000.1190.0100.0240.1250.0900.0200.0220.0000.0000.2070.2830.4050.1550.0400.1100.6490.1100.0000.1420.1060.0870.1460.0290.1060.012
Grid Production PossiblePower Max. [W]0.0040.0000.0000.0000.0000.0000.0850.0950.0360.0260.1830.1550.1260.1480.0040.0030.0070.0230.0060.0000.0860.0630.0800.0730.0470.0680.0430.0170.0190.0120.0290.0350.0210.1650.1750.0740.1650.0130.0000.0300.2200.2430.2450.2570.0000.3461.0000.2620.3560.2910.6760.1880.2920.1510.1430.0570.1400.0000.0000.0000.0130.0120.0240.0000.0000.0000.0000.1180.1150.0530.1770.0170.0000.1190.0160.0330.0470.0770.0370.0100.0000.0000.1790.0900.2270.1610.0500.1120.2990.1330.0000.1770.1490.0630.1770.0340.0900.002
Grid Production PossiblePower Min. [W]0.0040.0000.0000.0000.0000.0000.0930.0510.1010.0450.2070.1120.1680.2500.0040.0110.0250.0130.0000.0000.0370.0380.0430.0460.0530.0270.0340.0350.0050.0050.0300.0330.0210.1440.1420.1720.2650.0140.0230.0400.2390.2770.2830.2900.0000.4080.2621.0000.3140.3310.2590.5340.3030.1470.1110.0670.1590.0000.0000.0060.0350.0230.0290.0270.0120.0000.0110.0710.0800.0680.2090.0070.0000.0720.0050.0030.0990.1010.0080.0050.0000.0000.1880.1090.2880.1630.0000.2220.3340.0920.0000.1460.1210.1500.2180.0240.0930.023
Grid Production PossiblePower StdDev [W]0.0050.0000.0000.0000.0090.0000.0710.0820.0340.1260.2570.1730.1820.2310.0050.0160.0000.0000.0050.0180.0500.0370.0720.0590.0480.0410.0520.0200.0160.0100.0400.0510.0400.1780.1910.0830.2290.0240.0060.0380.2480.2740.2790.2940.0000.4090.3560.3141.0000.3480.3180.2280.7440.2120.1850.0840.1370.0000.0000.0000.0420.0320.0410.0180.0000.0170.0010.1120.1100.0680.2380.0240.0000.1130.0240.0370.0750.1160.0240.0040.0000.0000.2230.1030.2960.2040.0580.1440.3450.1620.0000.1750.1650.0690.1870.0300.1080.000
Grid Production Power Avg. [W]0.0040.0040.0000.0000.0200.0030.2010.0790.0700.0400.1890.1280.1550.1590.0000.0300.0060.0210.0000.0110.0660.0640.0820.0440.0390.0370.0260.0100.0140.0000.0690.0680.0470.1510.1290.1300.1650.0280.0120.0820.2470.6660.6610.6850.0000.6700.2910.3310.3481.0000.3580.4030.4010.2280.1510.1370.1640.0090.0000.0020.0560.0510.0540.0090.0000.0080.0240.1700.1460.0730.1850.0070.0070.1660.0160.0330.1290.1260.0220.0160.0000.0000.3380.2700.4190.2670.0160.1140.8500.1640.0000.1530.1020.1100.1530.0270.0880.012
Grid Production Power Max. [W]0.0000.0340.0000.0040.0140.0000.0790.0870.0530.0390.1710.1380.1120.1120.0000.0190.0000.0380.0000.0000.0690.0560.0800.0680.0430.0670.0490.0140.0140.0180.0710.0650.0560.1520.1750.0680.1520.0260.0120.0590.2410.3180.3160.3430.0000.2990.6760.2590.3180.3581.0000.2370.3310.1850.1580.0690.1300.0020.0120.0040.0260.0210.0310.0110.0080.0000.0000.1200.1170.0250.1760.0350.0330.1160.0330.0430.0570.0710.0330.0140.0000.0000.2210.0600.2420.2110.0000.0890.3500.1360.0080.1620.1390.0530.1580.0230.0820.000
Grid Production Power Min. [W]0.0200.0060.0000.0040.0090.0000.0830.0460.0870.0340.1580.0720.1410.1850.0050.0330.0000.0270.0000.0090.0220.0310.0480.0210.0350.0250.0490.0190.0140.0050.0400.0460.0420.1030.1060.1600.2170.0120.0130.0500.2000.3800.3740.3830.0000.2950.1880.5340.2280.4030.2371.0000.2870.1640.0940.1640.1630.0040.0000.0070.0420.0340.0330.0140.0000.0000.0060.0790.0670.0540.1610.0140.0090.0740.0220.0130.0740.1640.0180.0120.0000.0000.2110.0810.2790.1900.0170.1870.3880.1030.0000.1070.0810.1300.1740.0220.0870.008
Grid Production Power StdDev [W]0.0020.0270.0000.0000.0000.0050.0680.0790.0450.1200.2350.1190.1950.2510.0000.0150.0000.0100.0000.0000.0460.0420.0710.0530.0510.0430.0520.0130.0030.0000.0430.0490.0340.1690.1480.0940.2510.0180.0000.0440.2370.3190.3190.3420.0000.3650.2920.3030.7440.4010.3310.2871.0000.2510.1820.1130.1800.0000.0000.0040.0440.0300.0330.0170.0000.0070.0080.1540.1330.1010.2240.0350.0250.1500.0370.0520.0760.1190.0160.0100.0000.0000.2460.1230.2840.2270.0900.1480.3860.1860.0040.1680.1240.0750.2060.0170.0760.000
Grid Production ReactivePower Avg. [W]0.0000.0560.0110.0140.0390.1090.0390.0270.0750.0310.4250.1930.6380.5000.0000.0310.0090.0000.0050.0000.0350.0490.0360.0740.1140.0230.0280.0080.0330.0060.0250.0170.0120.2040.1810.3290.2050.0320.0370.0310.4670.2260.2300.2480.0170.1510.1510.1470.2120.2280.1850.1640.2511.0000.5930.4640.5140.0020.0000.0000.0340.0220.0270.0370.0000.0210.0150.1780.1560.3480.6510.0840.0500.1780.0790.1090.1340.0820.0000.0230.0110.0110.6330.1740.2910.6910.2000.5430.2130.6870.0820.2210.1550.2400.1620.0390.0390.094
Grid Production ReactivePower Max. [W]0.0000.0350.0000.0000.0200.0430.0430.0380.0720.0270.2970.1520.4710.3710.0020.0000.0080.0050.0110.0000.0440.0420.0490.0630.0860.0330.0000.0100.0380.0080.0340.0300.0210.1280.1380.2220.1450.0280.0230.0300.3350.1380.1380.1490.0110.1410.1430.1110.1850.1510.1580.0940.1820.5931.0000.3810.3980.0120.0090.0000.0250.0200.0250.0200.0150.0310.0080.1020.0870.2600.4730.0420.0300.1000.0410.0550.1250.1350.0070.0270.0000.0000.4050.1400.2440.3940.2170.3810.1530.4720.0380.1390.1210.1660.1130.0220.0510.046
Grid Production ReactivePower Min. [W]0.0000.0610.0070.0080.0230.0620.0340.0270.0680.0300.2420.0910.3580.2840.0050.0160.0140.0000.0100.0150.0430.0580.0290.0610.0910.0360.0050.0020.0280.0130.0300.0360.0270.1580.0920.2400.1590.0200.0330.0420.2550.1350.1380.1520.0120.0610.0570.0670.0840.1370.0690.1640.1130.4640.3811.0000.3310.0160.0080.0000.0460.0440.0390.0200.0000.0180.0080.1170.0990.1750.3400.0720.0510.1150.0690.0860.0820.2130.0000.0100.0070.0070.3740.0830.1320.3790.0680.3020.1270.3270.0670.1630.0770.2040.1330.0150.0150.067
Grid Production ReactivePower StdDev [W]0.0060.0460.0000.0060.0000.0320.0240.0210.0600.0260.2500.0670.4070.4130.0060.0310.0000.0080.0160.0180.0320.0270.0200.0520.0550.0260.0320.0220.0260.0020.0080.0130.0000.1080.0950.2010.2340.0280.0110.0210.3000.1470.1490.1570.0100.1160.1400.1590.1370.1640.1300.1630.1800.5140.3980.3311.0000.0070.0000.0000.0110.0110.0180.0190.0230.0000.0150.0930.0760.2750.4360.0490.0370.0910.0440.0620.0460.1150.0170.0150.0000.0000.3540.1730.2210.3540.1740.4490.1570.4030.0520.1000.0850.1360.1990.0320.0310.072
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0060.0060.0080.0040.0000.0000.0000.0000.0120.0120.0050.0000.0000.0000.0050.0000.0000.0000.0000.0000.0040.0080.0000.0070.0000.0040.0000.0000.0020.0000.0070.0000.0000.0000.0000.0000.0000.0090.0020.0040.0000.0020.0120.0160.0071.0000.5440.5310.0000.0020.0100.0000.0000.0000.0040.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0050.0070.0000.0000.0010.0150.0000.0040.0050.0120.0120.0130.0000.0000.0050.0120.0140.0000.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0000.0000.0050.0000.0020.0000.0000.0000.0110.0000.0000.0090.0080.0000.0000.0040.0000.0000.0080.0110.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0020.0170.0090.0150.0000.0000.0000.0000.0010.0130.0120.0000.0000.0050.0000.0000.0000.0000.0120.0000.0000.0000.0090.0080.0000.5441.0000.5640.0010.0000.0180.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0090.0070.0160.0000.0000.0140.015
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0000.0000.0000.0070.0000.0040.0000.0070.0000.0000.0000.0070.0090.0000.0000.0000.0000.0000.0040.0140.0070.0000.0000.0040.0000.0090.0000.0000.0000.0000.0090.0000.0020.0000.0000.0000.0000.0000.0060.0000.0150.0000.0000.0000.0000.0060.0000.0020.0040.0070.0040.0000.0000.0000.0000.5310.5641.0000.0000.0000.0190.0090.0000.0000.0060.0000.0000.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0050.0110.0000.0000.0000.0000.0000.0000.0120.0050.0000.0190.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0040.0000.0000.0050.0000.0230.0240.0160.0360.0560.0210.0400.0330.0080.0000.0000.0240.0000.2150.0600.0680.0560.0540.0570.0410.0040.0170.0240.1710.0910.0730.0800.0580.0460.0450.0430.0000.0300.3090.0390.0620.0740.0720.0050.0350.0130.0350.0420.0560.0260.0420.0440.0340.0250.0460.0110.0000.0010.0001.0000.3940.2890.0160.0000.0110.0080.0280.0220.0000.0240.0000.0000.0290.0000.0100.0300.0310.0070.0000.0000.0000.0460.0160.0110.0480.0350.0060.0520.0000.0000.0570.0440.0540.0300.0080.0240.009
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0060.0000.0030.0230.0000.0340.0170.0080.0240.0300.0170.0260.0240.0200.0000.0000.0130.0000.2690.0690.0640.0470.0490.0480.0340.0000.0150.0250.1720.0740.0820.0740.0500.0330.0320.0470.0160.0400.1820.0240.0660.0680.0620.0100.0330.0120.0230.0320.0510.0210.0340.0300.0220.0200.0440.0110.0020.0000.0000.3941.0000.4570.0250.0100.0070.0130.0240.0210.0000.0060.0000.0080.0240.0000.0040.0310.0270.0260.0000.0000.0000.0380.0180.0000.0450.0290.0000.0470.0000.0000.0450.0320.0430.0320.0000.0130.000
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0000.0000.0000.0120.0000.0280.0140.0070.0200.0300.0000.0290.0160.0140.0000.0140.0170.0040.2590.0620.0770.0520.0580.0470.0410.0040.0150.0350.1640.0790.0970.0770.0450.0420.0380.0370.0000.0430.2090.0250.0630.0750.0720.0000.0370.0240.0290.0410.0540.0310.0330.0330.0270.0250.0390.0180.0100.0180.0190.2890.4571.0000.0220.0000.0000.0080.0180.0200.0000.0150.0000.0000.0180.0000.0000.0370.0210.0200.0000.0000.0000.0340.0160.0100.0390.0260.0000.0510.0000.0000.0440.0400.0520.0200.0140.0190.000
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0070.0000.0280.0130.0160.0040.0190.0250.0070.0380.0210.0300.0300.0000.0110.0160.0140.0280.0170.0060.0000.0000.0090.0270.0060.0030.0180.0250.0170.0000.0160.0130.0220.0310.0330.0170.0490.0460.0130.0380.0170.0200.0160.0000.0060.0000.0270.0180.0090.0110.0140.0170.0370.0200.0200.0190.0000.0000.0090.0160.0250.0221.0000.0270.0210.0000.0100.0110.0170.0350.0140.0060.0100.0120.0160.0280.0250.0000.0340.0000.0000.0350.0120.0170.0410.0080.0370.0110.0200.0130.0280.0200.0250.0150.0150.0040.019
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0100.0000.0000.0060.0150.0000.0000.0100.0000.0130.0210.0130.0180.0000.0000.0170.0350.0120.0190.0000.0000.0070.0150.0080.0100.0000.0510.0130.0000.0090.0390.0130.0130.0030.0090.0000.0210.0310.0180.0000.0000.0000.0000.0000.0090.0000.0120.0000.0000.0080.0000.0000.0000.0150.0000.0230.0000.0000.0000.0000.0100.0000.0271.0000.2010.2390.0000.0040.0620.0320.0000.0120.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0650.0000.0040.0170.0010.0000.0090.0000.0050.0000.0080.0000.0000.0000.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0050.0000.0130.0000.0000.0000.0000.0040.0110.0130.0170.0210.0210.0000.0030.0520.0330.0530.0000.0100.0070.0160.0120.0090.0000.0000.0450.0130.0000.0280.0170.0260.0090.0000.0110.0000.0000.0380.0000.0000.0000.0000.0000.0000.0170.0000.0000.0170.0080.0000.0000.0070.0210.0310.0180.0000.0000.0000.0000.0110.0070.0000.0210.2011.0000.1800.0050.0090.0530.0420.0000.0000.0050.0000.0000.0060.0040.0060.0930.0000.0000.0090.0510.0170.0050.0060.0170.0120.0140.0000.0030.0000.0030.0000.0090.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0240.0000.0000.0000.0000.0040.0130.0060.0000.0200.0080.0160.0260.0000.0000.0310.0290.0130.0170.0000.0000.0000.0000.0160.0000.0000.0240.0000.0080.0150.0090.0180.0090.0000.0000.0000.0060.0310.0000.0000.0030.0020.0010.0010.0230.0000.0110.0010.0240.0000.0060.0080.0150.0080.0080.0150.0040.0000.0060.0080.0130.0080.0000.2390.1801.0000.0080.0070.0530.0340.0000.0110.0080.0000.0000.0000.0000.0000.0130.0000.0000.0050.0730.0200.0000.0190.0230.0260.0150.0110.0050.0000.0000.0100.0080.0000.002
HourCounters Average AlarmActive Avg. [h]0.0000.2010.0580.0130.0200.0940.0000.0000.0140.0000.1790.1090.1520.1370.0300.0300.0220.0000.0150.0000.0460.0480.0740.0420.0580.0210.0890.0040.0000.0000.0000.0000.0000.1370.0980.1230.1250.0000.0040.0290.1420.1540.1510.1530.0000.1180.1180.0710.1120.1700.1200.0790.1540.1780.1020.1170.0930.0000.0000.0000.0280.0240.0180.0100.0000.0050.0081.0000.7860.2340.0270.4330.2200.9650.4280.6340.1030.0210.0000.0190.0580.0580.2310.1760.0000.2220.0760.0180.1660.1270.0170.1510.0830.1060.1010.0350.0000.004
HourCounters Average AmbientOk Avg. [h]0.0000.2820.1080.0070.0210.0870.0000.0000.0210.0030.1520.0980.1150.1150.0440.0410.0130.0000.0060.0010.0310.0340.0460.0270.0370.0210.0690.0000.0000.0000.0000.0000.0000.1160.0890.0900.0980.0020.0000.0300.1270.1380.1350.1350.0000.1110.1150.0800.1100.1460.1170.0670.1330.1560.0870.0990.0760.0000.0000.0000.0220.0210.0200.0110.0040.0090.0070.7861.0000.2020.0170.6540.3410.8190.5560.4600.1250.0300.0000.0100.1080.1080.1970.1580.0000.1830.0650.0050.1440.1060.0120.1300.0760.0760.0790.0220.0000.015
HourCounters Average Gen1 Avg. [h]0.0000.0070.0000.0170.0110.0130.0160.0160.0660.0120.1630.0110.3100.2510.0180.0400.0130.0380.0000.0000.0130.0160.0460.0340.0660.0000.0110.0230.0000.0040.0120.0130.0120.0440.0690.2030.0180.0050.0160.0210.0000.0690.0660.0680.0050.0610.0530.0680.0680.0730.0250.0540.1010.3480.2600.1750.2750.0060.0040.0140.0000.0000.0000.0170.0620.0530.0530.2340.2021.0000.5270.0530.0100.2350.0510.0930.0000.0100.0060.0110.0000.0000.0490.5810.3700.0360.2850.1960.0700.2600.0090.0580.0500.1690.0000.0150.0100.000
HourCounters Average Gen2 Avg. [h]0.0000.0380.0250.0200.0290.0810.0500.0290.0670.0250.3950.1840.5430.4320.0070.0380.0100.0000.0210.0000.0450.0510.0280.0880.1420.0310.0160.0410.0420.0190.0200.0050.0040.2130.1820.4060.2170.0330.0460.0130.5020.1330.1350.1520.0090.1980.1770.2090.2380.1850.1760.1610.2240.6510.4730.3400.4360.0000.0000.0000.0240.0060.0150.0350.0320.0420.0340.0270.0170.5271.0000.0300.0480.0350.0030.0500.1320.0770.0090.0330.0250.0250.6110.2690.4980.5400.1020.5150.1850.4640.0560.2340.1590.3110.1690.0400.0670.082
HourCounters Average GridOk Avg. [h]0.0000.4210.1610.0070.0000.0690.0000.0000.0290.0000.0870.0410.0540.0630.0650.0300.0200.0000.0250.0010.0000.0000.0000.0000.0000.0190.0360.0060.0000.0040.0000.0000.0000.0350.0380.0360.0390.0110.0000.0000.0760.0070.0060.0060.0000.0130.0170.0070.0240.0070.0350.0140.0350.0840.0420.0720.0490.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.4330.6540.0530.0301.0000.5090.4770.8290.6870.0510.0170.0000.0210.1610.1610.1070.0000.0000.1030.0000.0200.0080.0530.0240.0390.0310.0270.0300.0170.0000.000
HourCounters Average GridOn Avg. [h]0.0000.7990.3370.0000.0000.0250.0000.0000.0580.0000.0520.0200.0400.0440.0920.0530.0000.0180.0200.0000.0000.0000.0000.0000.0000.0000.0150.0090.0000.0050.0000.0000.0000.0150.0140.0350.0110.0000.0000.0000.0430.0000.0000.0060.0000.0000.0000.0000.0000.0070.0330.0090.0250.0500.0300.0510.0370.0000.0000.0000.0000.0080.0000.0060.0120.0000.0110.2200.3410.0100.0480.5091.0000.2210.2630.3250.1010.0000.0000.0130.3370.3370.0610.0000.0000.0640.0000.0120.0000.0340.0220.0180.0050.0290.0100.0140.0000.000
HourCounters Average Run Avg. [h]0.0000.1880.0990.0120.0210.0980.0000.0000.0100.0000.1810.1080.1550.1360.0260.0300.0220.0000.0150.0000.0470.0480.0740.0430.0580.0210.0860.0070.0000.0000.0000.0000.0000.1390.0970.1270.1250.0000.0000.0290.1430.1530.1490.1490.0000.1190.1190.0720.1130.1660.1160.0740.1500.1780.1000.1150.0910.0000.0000.0000.0290.0240.0180.0100.0000.0050.0080.9650.8190.2350.0350.4770.2211.0000.4070.6570.1040.0220.0000.0190.0990.0990.2300.1780.0000.2150.0770.0180.1620.1240.0100.1520.0840.1100.1000.0310.0000.005
HourCounters Average ServiceOn Avg. [h]0.0000.2160.1080.0000.0000.0630.0000.0000.0000.0000.0740.0430.0390.0610.0360.0000.0200.0000.0120.0110.0000.0000.0000.0000.0000.0250.0300.0000.0000.0050.0000.0000.0000.0300.0390.0160.0320.0130.0000.0000.0720.0110.0100.0150.0000.0100.0160.0050.0240.0160.0330.0220.0370.0790.0410.0690.0440.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.4280.5560.0510.0030.8290.2630.4071.0000.5990.0260.0170.0000.0180.1080.1080.1030.0000.0000.1030.0000.0120.0220.0540.0280.0340.0290.0080.0230.0130.0000.000
HourCounters Average TurbineOk Avg. [h]0.0000.2780.1460.0130.0000.0910.0000.0000.0140.0000.1220.0670.0930.0780.0390.0210.0350.0070.0400.0000.0140.0160.0330.0150.0170.0200.0660.0170.0000.0000.0000.0000.0000.0630.0570.0730.0580.0000.0070.0000.1030.0280.0270.0270.0000.0240.0330.0030.0370.0330.0430.0130.0520.1090.0550.0860.0620.0000.0000.0000.0100.0040.0000.0160.0000.0000.0000.6340.4600.0930.0500.6870.3250.6570.5991.0000.0310.0120.0000.0330.1460.1460.1390.0210.0000.1390.0050.0200.0290.0750.0210.0700.0500.0610.0440.0260.0080.000
HourCounters Average WindOk Avg. [h]0.0000.0820.0280.0120.0160.0180.0510.0460.0360.0000.1100.1750.1230.0910.0090.0000.0110.0000.0230.0130.0340.0190.0000.0460.0570.0210.0420.0160.0170.0530.0180.0270.0220.0260.0350.1170.0430.0210.0190.0110.2240.1480.1430.1170.0000.1250.0470.0990.0750.1290.0570.0740.0760.1340.1250.0820.0460.0000.0000.0000.0300.0310.0370.0280.0000.0060.0000.1030.1250.0000.1320.0510.1010.1040.0260.0311.0000.0480.0200.0080.0280.0280.2210.0060.1090.1820.0570.1170.1290.0640.0110.0260.0160.1100.0080.0160.0170.017
HourCounters Average Yaw Avg. [h]0.0130.0000.0000.0000.0310.0120.0210.0290.0220.0570.0820.0400.0450.0990.0000.0070.0000.0070.0000.0110.0100.0000.0220.0080.0160.0000.0230.0000.0160.0180.0120.0190.0120.0580.0560.0320.1140.0160.0100.0000.1120.1040.1060.1060.0000.0900.0770.1010.1160.1260.0710.1640.1190.0820.1350.2130.1150.0000.0000.0000.0310.0270.0210.0250.0000.0040.0000.0210.0300.0100.0770.0170.0000.0220.0170.0120.0481.0000.0090.0000.0000.0000.1110.0170.1000.1030.0280.0950.1250.0490.0080.0530.0560.0340.0920.0040.0430.012
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0000.0080.0000.0150.0000.0000.0000.0000.0000.0000.0060.0000.0170.0000.0000.0000.0000.0130.0050.0120.0000.0100.0070.0250.0000.0000.0110.0040.0140.0150.0270.0120.0000.0030.0000.0160.0070.0150.0000.0180.0160.0210.0000.0200.0370.0080.0240.0220.0330.0180.0160.0000.0070.0000.0170.0050.0000.0000.0070.0260.0200.0000.0000.0060.0000.0000.0000.0060.0090.0000.0000.0000.0000.0000.0200.0091.0000.0140.0000.0000.0000.0140.0000.0000.0120.0040.0250.0070.0000.0040.0040.0000.0220.0200.0010.000
Nacelle Temp. Avg. [°C]0.0000.0100.0000.0680.0000.0000.0090.0000.0000.0030.0250.0140.0310.0150.0120.0000.0740.0110.1200.0000.0000.0040.0000.0030.0000.0000.0320.0240.0130.0000.0000.0000.0120.0190.0100.0220.0120.0810.0720.0000.0130.0130.0100.0160.0040.0220.0100.0050.0040.0160.0140.0120.0100.0230.0270.0100.0150.0070.0000.0000.0000.0000.0000.0340.0060.0930.0130.0190.0100.0110.0330.0210.0130.0190.0180.0330.0080.0000.0141.0000.0000.0000.0260.0000.0210.0210.0210.0200.0160.0260.0000.0280.0130.0160.0060.0310.0000.007
Power factor set point0.0000.3090.8750.0000.0000.0240.0000.0000.0000.0000.0230.0220.0320.0000.0000.0000.0000.0150.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0090.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0580.1080.0000.0250.1610.3370.0990.1080.1460.0280.0000.0000.0001.0000.8750.0300.0000.0000.0280.0000.0000.0000.0150.0000.0000.0000.0180.0000.0000.0000.000
Power factor set point source0.0000.3090.8750.0000.0000.0240.0000.0000.0000.0000.0230.0220.0320.0000.0000.0000.0000.0150.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0090.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0580.1080.0000.0250.1610.3370.0990.1080.1460.0280.0000.0000.0000.8751.0000.0300.0000.0000.0280.0000.0000.0000.0150.0000.0000.0000.0180.0000.0000.0000.000
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.0690.0300.0090.0440.1110.0510.0280.0470.0290.3720.2430.4430.3370.0000.0340.0000.0320.0160.0000.0690.0810.0480.1060.1430.0550.0340.0120.0470.0260.0510.0340.0310.2800.1930.3760.2700.0370.0460.0240.6190.2780.2650.2980.0070.2070.1790.1880.2230.3380.2210.2110.2460.6330.4050.3740.3540.0010.0000.0000.0460.0380.0340.0350.0000.0090.0050.2310.1970.0490.6110.1070.0610.2300.1030.1390.2210.1110.0000.0260.0300.0301.0000.0330.1760.7870.0360.4130.3760.4510.0850.2960.1710.2840.2220.0570.0680.109
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0000.0000.0130.0000.0070.0960.0460.0520.0240.0760.0000.1730.1440.0110.0290.0120.0460.0000.0150.0650.0630.0520.0700.0610.0090.0000.0200.0040.0000.0000.0000.0050.0460.0030.1620.0110.0260.0140.0460.0000.2000.1960.1930.0000.2830.0900.1090.1030.2700.0600.0810.1230.1740.1400.0830.1730.0150.0030.0170.0160.0180.0160.0120.0650.0510.0730.1760.1580.5810.2690.0000.0000.1780.0000.0210.0060.0170.0140.0000.0000.0000.0331.0000.0110.0220.2000.0780.3540.1620.0080.0490.0000.1370.0300.0210.0090.011
Production LatestAverage Active Power Gen 2 Avg. [W]0.0020.0000.0000.0030.0090.0000.0980.0410.0730.0190.2470.1010.2790.2700.0000.0220.0110.0070.0000.0060.0000.0080.0420.0100.0200.0000.0170.0180.0080.0100.0230.0180.0110.0870.1460.1350.1460.0250.0120.0280.2110.3290.3350.3470.0000.4050.2270.2880.2960.4190.2420.2790.2840.2910.2440.1320.2210.0000.0000.0000.0110.0000.0100.0170.0000.0170.0200.0000.0000.3700.4980.0000.0000.0000.0000.0000.1090.1000.0000.0210.0000.0000.1760.0111.0000.1290.0910.2940.4300.1880.0000.0960.1160.1110.1060.0060.0990.000
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0000.0660.0280.0090.0480.1350.0370.0250.0380.0240.3470.2530.4080.3150.0080.0310.0050.0360.0120.0000.0620.0790.0480.1020.1360.0500.0430.0120.0480.0280.0470.0370.0350.2780.2110.3360.2600.0380.0410.0300.5750.2530.2590.2750.0080.1550.1610.1630.2040.2670.2110.1900.2270.6910.3940.3790.3540.0040.0000.0050.0480.0450.0390.0410.0040.0050.0000.2220.1830.0360.5400.1030.0640.2150.1030.1390.1820.1030.0000.0210.0280.0280.7870.0220.1291.0000.0430.3990.2550.5350.1080.2930.1850.2470.2120.0610.0490.119
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0000.0000.0000.0050.0120.0000.0000.0090.0120.0830.0170.1910.1590.0080.0000.0140.0150.0170.0090.0090.0060.0170.0000.0000.0040.0180.0000.0000.0190.0370.0280.0400.0210.0270.0290.0050.0190.0000.0080.0590.0000.0000.0000.0000.0400.0500.0000.0580.0160.0000.0170.0900.2000.2170.0680.1740.0050.0000.0110.0350.0290.0260.0080.0170.0060.0190.0760.0650.2850.1020.0000.0000.0770.0000.0050.0570.0280.0120.0210.0000.0000.0360.2000.0910.0431.0000.0640.0190.6940.0210.0000.0000.0090.0260.0000.0220.022
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0170.0000.0120.0160.0390.0050.0000.0620.0190.2630.0730.4630.5060.0000.0210.0000.0160.0210.0190.0030.0180.0020.0280.0500.0000.0000.0370.0330.0000.0000.0050.0000.1070.1190.2580.2950.0300.0310.0100.4110.0660.0750.0750.0120.1100.1120.2220.1440.1140.0890.1870.1480.5430.3810.3020.4490.0120.0000.0000.0060.0000.0000.0370.0010.0170.0230.0180.0050.1960.5150.0200.0120.0180.0120.0200.1170.0950.0040.0200.0000.0000.4130.0780.2940.3990.0641.0000.1150.4120.1160.1140.1020.1770.2290.0200.0600.141
Production LatestAverage Total Active Power Avg. [W]0.0040.0000.0000.0000.0170.0080.1930.0780.0720.0420.1920.1310.1600.1590.0000.0330.0070.0160.0000.0000.0720.0610.0890.0470.0420.0340.0250.0120.0160.0000.0610.0650.0460.1540.1280.1290.1590.0350.0160.0750.2480.6350.6230.6580.0000.6490.2990.3340.3450.8500.3500.3880.3860.2130.1530.1270.1570.0120.0000.0000.0520.0470.0510.0110.0000.0120.0260.1660.1440.0700.1850.0080.0000.1620.0220.0290.1290.1250.0250.0160.0000.0000.3760.3540.4300.2550.0190.1151.0000.1560.0030.1540.1040.1110.1530.0290.0940.014
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0380.0150.0110.0220.0730.0290.0140.0500.0020.3030.1520.4570.3480.0060.0200.0120.0000.0230.0070.0450.0390.0360.0650.0800.0320.0360.0070.0270.0000.0000.0000.0070.1720.1220.2380.1320.0410.0230.0070.3220.1480.1500.1610.0040.1100.1330.0920.1620.1640.1360.1030.1860.6870.4720.3270.4030.0130.0000.0000.0000.0000.0000.0200.0090.0140.0150.1270.1060.2600.4640.0530.0340.1240.0540.0750.0640.0490.0070.0260.0150.0150.4510.1620.1880.5350.6940.4120.1561.0000.0530.1640.1210.1640.1280.0270.0160.058
Reactive power generator 0,Total accumulated [var]0.0000.0350.0000.0000.0000.0050.0000.0000.0000.0000.0220.0000.0560.0710.0000.0040.0000.0140.0130.0120.0060.0060.0000.0000.0070.0000.0140.0000.0090.0000.0090.0000.0110.0250.0000.0610.0560.0080.0000.0070.0730.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0040.0820.0380.0670.0520.0000.0000.0000.0000.0000.0000.0130.0000.0000.0110.0170.0120.0090.0560.0240.0220.0100.0280.0210.0110.0080.0000.0000.0000.0000.0850.0080.0000.1080.0210.1160.0030.0531.0000.0280.0100.0440.0400.0030.0000.235
Rotor RPM Avg. [RPM]0.0000.0140.0000.0100.0220.0980.1030.0350.0600.0210.2580.1140.2230.1880.0000.0100.0030.0300.0100.0300.1280.1460.1570.1700.2080.1670.0400.0080.0610.0430.0410.0470.0510.7390.3240.3680.4170.0230.0420.0050.2100.1400.1350.1420.0000.1420.1770.1460.1750.1530.1620.1070.1680.2210.1390.1630.1000.0000.0090.0000.0570.0450.0440.0280.0050.0030.0050.1510.1300.0580.2340.0390.0180.1520.0340.0700.0260.0530.0040.0280.0000.0000.2960.0490.0960.2930.0000.1140.1540.1640.0281.0000.2900.3400.3810.0540.0220.059
Rotor RPM Max. [RPM]0.0000.0060.0000.0050.0310.0900.0670.0560.0480.0330.2040.2240.1160.1250.0080.0120.0000.0130.0120.0130.0660.0600.0610.0700.0970.0890.0750.0000.0360.0220.0270.0300.0280.3520.7420.1260.2600.0140.0300.0270.1460.0960.0950.0980.0000.1060.1490.1210.1650.1020.1390.0810.1240.1550.1210.0770.0850.0050.0070.0000.0440.0320.0400.0200.0000.0000.0000.0830.0760.0500.1590.0310.0050.0840.0290.0500.0160.0560.0040.0130.0000.0000.1710.0000.1160.1850.0000.1020.1040.1210.0100.2901.0000.1110.2060.0530.0560.025
Rotor RPM Min. [RPM]0.0000.0280.0180.0180.0130.0560.0780.0310.0920.0140.2090.0690.2870.2050.0000.0030.0070.0050.0220.0360.0870.1140.0880.1430.1760.0790.0000.0250.0330.0380.0380.0350.0260.3270.1160.7690.2270.0190.0470.0390.2140.0900.0870.0870.0000.0870.0630.1500.0690.1100.0530.1300.0750.2400.1660.2040.1360.0120.0160.0120.0540.0430.0520.0250.0080.0030.0000.1060.0760.1690.3110.0270.0290.1100.0080.0610.1100.0340.0000.0160.0180.0180.2840.1370.1110.2470.0090.1770.1110.1640.0440.3400.1111.0000.1880.0240.0200.060
Rotor RPM StdDev [RPM]0.0000.0290.0000.0000.0000.0480.0430.0250.0320.0490.1830.0640.1790.3140.0080.0240.0030.0390.0190.0000.0830.0860.0640.0910.0840.0930.0550.0190.0370.0100.0200.0320.0350.3940.2330.2130.6960.0160.0200.0160.2090.1230.1220.1240.0000.1460.1770.2180.1870.1530.1580.1740.2060.1620.1130.1330.1990.0140.0000.0050.0300.0320.0200.0150.0000.0000.0100.1010.0790.0000.1690.0300.0100.1000.0230.0440.0080.0920.0220.0060.0000.0000.2220.0300.1060.2120.0260.2290.1530.1280.0400.3810.2060.1881.0000.0370.0630.080
Spinner Temp. Avg. [°C]0.0000.0110.0000.0200.0180.0520.0000.0000.0120.0000.0390.0410.0260.0170.0000.0710.0040.0200.0000.0030.0000.0140.0070.0200.0230.0090.0470.0000.0290.0000.0160.0280.0220.0530.0600.0350.0420.0200.0250.0090.0360.0190.0210.0220.0000.0290.0340.0240.0300.0270.0230.0220.0170.0390.0220.0150.0320.0000.0000.0000.0080.0000.0140.0150.0000.0090.0080.0350.0220.0150.0400.0170.0140.0310.0130.0260.0160.0040.0200.0310.0000.0000.0570.0210.0060.0610.0000.0200.0290.0270.0030.0540.0530.0240.0371.0000.0390.000
Total Active power [W]0.0000.0000.0000.0050.0000.0260.0000.0000.0000.0000.0680.0840.0430.0630.0030.0000.0000.0170.0110.0000.0000.0060.0000.0000.0000.0000.0660.0000.0110.0080.0360.0300.0260.0170.0680.0270.0730.0250.0000.0270.0810.0600.0710.0630.0000.1060.0900.0930.1080.0880.0820.0870.0760.0390.0510.0150.0310.0000.0140.0190.0240.0130.0190.0040.0000.0000.0000.0000.0000.0100.0670.0000.0000.0000.0000.0080.0170.0430.0010.0000.0000.0000.0680.0090.0990.0490.0220.0600.0940.0160.0000.0220.0560.0200.0630.0391.0000.000
Total reactive power [var]0.0000.0000.0000.0000.0000.0140.0020.0000.0000.0000.0430.0210.0730.1010.0000.0000.0000.0200.0000.0100.0000.0070.0060.0000.0190.0000.0190.0090.0110.0000.0110.0070.0060.0570.0090.0840.0960.0100.0070.0080.0850.0070.0070.0130.0000.0120.0020.0230.0000.0120.0000.0080.0000.0940.0460.0670.0720.0000.0150.0000.0090.0000.0000.0190.0000.0000.0020.0040.0150.0000.0820.0000.0000.0050.0000.0000.0170.0120.0000.0070.0000.0000.1090.0110.0000.1190.0220.1410.0140.0580.2350.0590.0250.0600.0800.0000.0001.000

Missing values

2025-05-15T14:18:56.761375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-15T14:18:57.493906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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72020-01-01 01:10:0000000100001000000010000000000000000111000000000000000000000000000000000000000000000000000000000010000000000000001000000000000000
82020-01-01 01:20:0000000000001000000000000110000000000001100000000000000000000000000000000000000010000000000000000000000000000000000000000000000000
92020-01-01 01:30:0000000000101000000000100000000000000011000000000000000000000000000000000000000000000000000000000010000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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